\begin{tabular}{p{.45\textwidth}*{4}{r@{}l}}
\hline
\hline
& \multicolumn{2}{c}{Model 1} & \multicolumn{2}{c}{Model 2}  \\
\hline
treated             &      -4.262&** &      -7.752&***&      -3.872&** &      -7.265&***\\
                    &     (1.534)&   &     (2.442)&   &     (1.409)&   &     (2.249)&   \\
v04b                &       0.264&   &       0.651&*  &       0.193&   &       0.515&   \\
                    &     (0.169)&   &     (0.337)&   &     (0.196)&   &     (0.369)&   \\
population          &      -0.001&   &      -0.002&   &      -0.001&   &      -0.002&   \\
                    &     (0.002)&   &     (0.003)&   &     (0.001)&   &     (0.002)&   \\
v106                &       0.019&   &       0.028&   &       0.001&   &       0.006&   \\
                    &     (0.024)&   &     (0.033)&   &     (0.024)&   &     (0.035)&   \\
male                &      -1.417&*  &      -2.359&***&      -0.572&   &      -1.226&   \\
                    &     (0.570)&   &     (0.765)&   &     (0.542)&   &     (0.865)&   \\
riskloss            &      -0.399&   &      -0.690&   &      -0.424&   &      -0.855&   \\
                    &     (0.447)&   &     (0.661)&   &     (0.422)&   &     (0.643)&   \\
muslim              &      -0.512&   &      -0.897&   &       0.231&   &       0.026&   \\
                    &     (0.674)&   &     (1.330)&   &     (0.478)&   &     (0.742)&   \\
christian           &       0.612&   &       0.854&   &       0.785&   &       1.275&   \\
                    &     (0.535)&   &     (0.631)&   &     (0.558)&   &     (0.818)&   \\
education           &            &   &            &   &      -0.431&   &      -0.801&***\\
                    &            &   &            &   &     (0.234)&   &     (0.232)&   \\
income10k           &            &   &            &   &      -0.105&***&      -0.157&** \\
                    &            &   &            &   &     (0.018)&   &     (0.075)&   \\
v205                &            &   &            &   &      -0.019&   &      -0.733&   \\
                    &            &   &            &   &     (0.586)&   &     (1.030)&   \\
Constant               &       6.666&*  &       7.993&   &       6.786&** &       9.203&***\\
                    &     (2.988)&   &     (4.810)&   &     (2.034)&   &     (3.236)&   \\
var(e.DictatorTakeManna)&            &   &       8.657&*  &            &   &       7.320&*  \\
                    &            &   &     (4.442)&   &            &   &     (3.755)&   \\
\hline
N.obs.              &          47&   &          47&   &          47&   &          47&   \\
\hline \multicolumn{9}{p{\textwidth}} {\footnotesize{\textbf{Notes:} Dependent variable: coins appropriated by the dictator. Models 1 and 3: OLS regression, models 2 and 4: left-censored Tobit regression. All models include village fixed-effects. Robust standard errors clustered at the village level. Compared to models 1 and 2, models 3 and 4 controls for income, finance, and education levels. Controls include: age,  gender, religion, estimation of risk preferences. Symbols $***$, $**$, and $*$ indicate significance at the 1\%, 5\% and 10\% level, respectively.}} \end{tabular}
